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Record W4396991952 · doi:10.1681/asn.20213210s1381b

The Association of Body Mass Index with the Development of Metabolic Acidosis in Patients with CKD

2021· article· en· W4396991952 on OpenAlexaff
Nancy L. Reaven, Susan E. Funk, Vandana Mathur, Thomas W. Ferguson, Navdeep Tangri

Bibliographic record

VenueJournal of the American Society of Nephrology · 2021
Typearticle
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMetabolic acidosisBody mass indexMedicineInternal medicineAcidosisAssociation (psychology)Intensive care medicinePsychology

Abstract

fetched live from OpenAlex

Background: Bone is the largest body buffer and body mass index (BMI) is directly related to bone mass. We explored the relationship between BMI and incident metabolic acidosis in patients with CKD. Methods: Optum's de-identified Integrated Claims-Clinical dataset of US patients (2007-2019) was queried to identify patients with non-dialysis CKD stages 3-5 with 2 consecutive serum bicarbonate values in the normal range (22 to <30 mEq/L), 28-365 days apart, with data ≥12 months pre-index during which covariates were assessed. The first qualifying serum bicarbonate test established the index date. The primary exposure variable was BMI category (World Health Organization classification). Other exposures included hypertension diagnosis, triglycerides ≥1.7 mmol/L, HDL cholesterol ≤1 mmol/L in women or ≤0.9 mmol/L in men. Adjusted Cox Proportional Hazards models were performed to evaluate the time to development of new-onset metabolic acidosis (serum bicarbonate 12 to <22 mEq/L) over a follow-up period of ≤11.5 years. Other covariates included age, sex, race, education and income status, diabetes or heart failure, eGFR, log albumin-to-creatinine ratio, angiotensin converting enzyme inhibitors or angiotensin receptor blockers prescription, and diuretic prescription. Results: 97,294 patients qualified for this study. There was an inverse association between BMI category and the risk of developing metabolic acidosis. Compared to BMI category of 18.5-25, each incremental category of higher BMI was associated with a decreasing risk of developing metabolic acidosis: BMI 25 to <30, HR 0.866, 95% CI: 0.824-0.911; BMI 30 to <35, HR 0.770, 95% CI: 0.729-0.813; BMI 35 to <40, HR 0.664, 95% CI: 0.622-0.709; BMI 40+, HR 0.612, 95% CI: 0.571-0.655. Additionally, hypertension decreased and low HDL cholesterol and elevated triglycerides increased the risk of new-onset metabolic acidosis. Conclusions: In this large cohort of patients with CKD, an incremental increase in BMI was inversely associated with the development metabolic acidosis. The mechanism of this association merits further study. Funding: Commercial Support - Tricida, Inc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.143

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.226
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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